Daily and seasonal use of vocalizations by nesting black-tailed godwits
Data files
Sep 26, 2024 version files 968.09 KB
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Amplitude_measurements.txt
11.70 KB
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Leaving_nest_after_staccato_calls.txt
6.10 KB
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Nest_vocalizations_of_Black-tailed_Godwits.txt
946.11 KB
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README.md
4.17 KB
Sep 26, 2024 version files 968.09 KB
-
Amplitude_measurements.txt
11.70 KB
-
Leaving_nest_after_staccato_calls.txt
6.10 KB
-
Nest_vocalizations_of_Black-tailed_Godwits.txt
946.11 KB
-
README.md
4.17 KB
Abstract
Ground-nesting shorebirds must balance the need for acoustic communication at the nest with the constant threat posed by predators. Although it may seem likely that their calls are adapted to minimize detection by predators, little is known about how these birds communicate at the nest or whether they employ cryptic strategies to avoid predation. Using passive acoustic devices and software to analyse extensive acoustic data, we quantified and categorised the calls of black-tailed godwits (Limosa limosa limosa) recorded throughout the whole incubation at eight nests at a dairy farm in the Netherlands in March-June 2021. While incubating, godwits frequently use five main call types, with distinct diurnal patterns and high variation in the number of calls between breeding pairs. Birds used two quiet calls, one for communication at the nest and a second without an easily suggested meaning. Three loud calls were presumably used for predator alert, territory establishment and long-range communication. Interestingly, although nests were close to each other and exposed to the same aerial predators, the involvement of incubating birds in predator alert calling consistently differed. Furthermore, we described the relationship between the number of predator alert calls and the probability of a godwit flying off the nest. Our findings show that incubating godwits predominantly use loud vocalizations during the day, with only a few calls at night, which were more frequent on nights with a full moon. These descriptive findings for a single godwit community should now be expanded to other contexts, experimental situations, and shorebird species.
README: Daily and seasonal use of vocalizations by nesting black-tailed godwits
https://doi.org/10.5061/dryad.m37pvmdc2
Description of the data and file structure
This study focused on documenting vocalizations by nesting black-tailed godwits during incubation. Eight godwit nests were recorded using audio SM2 recorders with microphones placed near the nests to capture vocalizations during the incubation period (24–29 days). Video footage from five nests complemented the audio recordings. Recordings were processed into 3-second fragments and analyzed for vocalizations using spectrograms, which were categorized into call types through manual and machine-learning techniques
Files and variables
File: Amplitude_measurements.txt
Description:
Variables
- combined_types: names of five main call types
- energy: 'Loudness' (Average Power Density) dB FS measured in Raven for each call selection.
File: Leaving_nest_after_staccato_calls.txt
Description:
Variables
- nest_id: original ID of the godwit nest
- n_staccato_calls: number of staccato calls in a given call sequence
- bird_left: yes/no if a bird flew from the nest - based on the sound of wingbeats
- other_alarming_birds: yes/no presence of other godwits using staccato calls
- birds_mobbing: yes/no detected mobbing behaviour of breeding shorebirds
- notes_1: number of notes within 1st staccato call in given sequence
- notes_2: number of notes within 2nd staccato call in given sequence
- notes_3: number of notes within 3rd staccato call in given sequence
- notes_4: number of notes within 4th staccato call in given sequence
- notes_5: number of notes within 5th staccato call in given sequence
- notes_6: number of notes within 6th staccato call in given sequence
- notes_7: number of notes within 6th staccato call in given sequence
- notes_8: number of notes within 8th staccato call in given sequence
- notes_9: number of notes within 9th staccato call in given sequence
- mean_notes: mean number of notes across all staccato calls in a given sequence
File: Nest_vocalizations_of_Black-tailed_Godwits.txt
Description:
Variables
- nest_id: original ID of the godwit nest
- time_call: time when the call was uttered or the start of the acoustic event (sequence of multiple calls)
- combined_types: letter-based system for names of five main call types (A = harsh call, B = rhythmic call, C = staccato call, D = short call, E = long call)
- cat_new: detailed names of call types
- hour: hour when the call was uttered
- dates: date when the call was uttered
- day_period: based on the time_call and package suncalc defined day period (day/twilight/night)
- sincefirstegg: number of days since estimated first laid eggs
- full_days: number of days that were fully recorded (24 hrs)
Code/software
We recommend saving datasets to folder data, putting R scripts in folder scripts, and creating folder figs to save the figures. R version 4.3.1.
0_Libraries.R
Script with main libraries to run the other scripts.
Fig2_Amplitude comparison.R
The script includes Dunn's posthoc test for amplitude comparison and code to generate a figure of amplitude levels for five main calls.
Fig4_Number of acoustic events per nest and call type.R
Script to generate figure 4.
Fig5_Merging Fig5abc.R
Script to combine figures 5a, 5b and 5c by running the separate scripts.
Fig5a_Seasonal trends in number of calls.R
Separate script for Fig5a and GAMs.
Fig5b_Daily trends in number of calls.R
Separate script for Fig5b and GAMs.
Fig5c_Number of calls per nest and type, day vs night.R
Separate script for Fig5c.
Fig6_Use of staccato calls.R
Script to generate figure 6.
FigApp1_Overviev seasonal activity.R
Script to generate figure 1 in the supplementary material.
FigApp2_Overview daily activity.R
Script to generate figure 2 in the supplementary material.
Vocal activity in relation to moon illumination.R
Script to run correlation test between moon illumination and mean number of short and rhythmic calls.
Methods
The study was conducted in 2021 at a dairy farm near Wommels, NW Netherlands, focusing on breeding black-tailed godwits. Eight godwit nests were recorded using SM2 recorders with microphones placed near the nests to capture vocalizations during the incubation period (24–29 days). Video footage from five nests complemented the audio recordings. Recordings were processed into 3-second fragments and analyzed for vocalizations using spectrograms, which were categorized into call types through manual and machine-learning techniques. We detected 77 325 3 s fragments that contained calls at eight nests during 183 fully recorded days. To better represent an individual’s decision to call, we used ‘acoustic events’, whereby all calls of the same type that are uttered with pauses of maximally 30 seconds are considered one event. A total of 15,078 acoustic events were identified. Statistical analysis, including general additive models (GAMs), was used to analyze daily and seasonal variations in vocal activity. For details, see the methods section in the published article.